Tensor-networks-based learning of probabilistic cellular automata dynamics
Algorithms developed to solve many-body quantum problems, like tensor networks, can turn into powerful quantum-inspired tools to tackle issues in the classical domain. This work focuses on matrix product operators, a prominent numerical technique to study many-body quantum systems, especially in one...
Saved in:
| Main Authors: | Heitor P. Casagrande, Bo Xing, William J. Munro, Chu Guo, Dario Poletti |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
American Physical Society
2024-11-01
|
| Series: | Physical Review Research |
| Online Access: | http://doi.org/10.1103/PhysRevResearch.6.043202 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Probabilistic Cellular Automata Monte Carlo for the Maximum Clique Problem
by: Alessio Troiani
Published: (2024-09-01) -
Cities and cellular automata
by: Roger White
Published: (1998-01-01) -
Complex Dynamic Behaviors in Cellular Automata Rule 14
by: Qi Han, et al.
Published: (2012-01-01) -
Renormalisation of Quantum Cellular Automata
by: Lorenzo Siro Trezzini, et al.
Published: (2025-05-01) -
Simulation of earthquakes with cellular automata
by: P. G. Akishin, et al.
Published: (1998-01-01)